Prediction of coronary heart diseases using supervised machine learning algorithms

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Détails bibliographiques
Auteurs principaux:	Salam, Nazia Binte, Raisa, Samiha, Rashid, Rahela Atia, Noor, Asmita, Obaed, Sin-Sumbil Binte
Autres auteurs:	Choudhury, Najeefa Nikhat
Format:	Thèse
Langue:	English
Publié:	Brac University 2023
Sujets:	Cardiovascular disease Random forest algorithm K-NN Machine learning Computer algorithms
Accès en ligne:	http://hdl.handle.net/10361/18702

id	10361-18702
record_format	dspace
spelling	10361-187022023-07-10T21:03:18Z Prediction of coronary heart diseases using supervised machine learning algorithms Salam, Nazia Binte Raisa, Samiha Rashid, Rahela Atia Noor, Asmita Obaed, Sin-Sumbil Binte Choudhury, Najeefa Nikhat Hawlader, Ahanaf Hassan Department of Computer Science and Engineering, Brac University Cardiovascular disease Random forest algorithm K-NN Machine learning Computer algorithms This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 31-33). Cardiovascular disease is a leading cause of death worldwide. According to the Centers for Disease Control and Prevention, one person dies from heart disease every 36 seconds in the United States. In 2019, an estimated 17.9 million people died from CVD worldwide. High blood pressure, an unhealthy diet, high cholesterol, diabetes, air pollution, obesity, tobacco use, kidney disease, physical inactivity, harmful alcohol use, and stress can all contribute to it. Family history, ethnic background, sex, and age are some other contributing factors to a person’s risk of heart disease. This paper seeks to predict heart diseases using a dataset that has factors like age, sex, the number of cigarettes smoked, etc. This prediction will be done by analyzing different parameters like blood pressure, oxygen level, hemoglobin count, etc. which are the major deciding factors to measure heart risks. The research will use supervised Machine Learning (ML) algorithms such as decision tree (a classification algorithm that works on categorical as well as numerical data), K-Nearest Neighbor (K-NN), Random forest algorithm, etc. to provide an accurate prediction. After applying ML on medical data, the outcome will be used to conduct a comparative analysis to measure the efficiency of different ML algorithms in predicting cardiovascular diseases. Furthermore, the major objective of this research is to use the algorithms and process in Bangladeshi dataset and explore the result outcome and newer possibilities. Nazia Binte Salam Samiha Raisa Rahela Atia Rashid Asmita Noor Sin-Sumbil Binte Obaed B. Computer Science 2023-07-10T06:10:32Z 2023-07-10T06:10:32Z 2022 2022-05 Thesis ID 18301080 ID 18301156 ID 18301150 ID 19101640 ID 18301092 http://hdl.handle.net/10361/18702 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 33 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Cardiovascular disease Random forest algorithm K-NN Machine learning Computer algorithms
spellingShingle	Cardiovascular disease Random forest algorithm K-NN Machine learning Computer algorithms Salam, Nazia Binte Raisa, Samiha Rashid, Rahela Atia Noor, Asmita Obaed, Sin-Sumbil Binte Prediction of coronary heart diseases using supervised machine learning algorithms
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
author2	Choudhury, Najeefa Nikhat
author_facet	Choudhury, Najeefa Nikhat Salam, Nazia Binte Raisa, Samiha Rashid, Rahela Atia Noor, Asmita Obaed, Sin-Sumbil Binte
format	Thesis
author	Salam, Nazia Binte Raisa, Samiha Rashid, Rahela Atia Noor, Asmita Obaed, Sin-Sumbil Binte
author_sort	Salam, Nazia Binte
title	Prediction of coronary heart diseases using supervised machine learning algorithms
title_short	Prediction of coronary heart diseases using supervised machine learning algorithms
title_full	Prediction of coronary heart diseases using supervised machine learning algorithms
title_fullStr	Prediction of coronary heart diseases using supervised machine learning algorithms
title_full_unstemmed	Prediction of coronary heart diseases using supervised machine learning algorithms
title_sort	prediction of coronary heart diseases using supervised machine learning algorithms
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/18702
work_keys_str_mv	AT salamnaziabinte predictionofcoronaryheartdiseasesusingsupervisedmachinelearningalgorithms AT raisasamiha predictionofcoronaryheartdiseasesusingsupervisedmachinelearningalgorithms AT rashidrahelaatia predictionofcoronaryheartdiseasesusingsupervisedmachinelearningalgorithms AT noorasmita predictionofcoronaryheartdiseasesusingsupervisedmachinelearningalgorithms AT obaedsinsumbilbinte predictionofcoronaryheartdiseasesusingsupervisedmachinelearningalgorithms
_version_	1814309136599351296

Prediction of coronary heart diseases using supervised machine learning algorithms

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